hsv_filter = HsvFilter(0, 180, 129, 15, 229, 243, 143, 0, 67, 0)
loop_time = time()
while (True):
# get an updated image of the game
screenshot = wincap.get_screenshot()
# pre-process the image
processed_image = vision_limestone.apply_hsv_filter(screenshot, hsv_filter)
# do object detection
rectangles = vision_limestone.find(processed_image, 0.46)
# draw the detection results onto the original image
output_image = vision_limestone.draw_rectangles(screenshot, rectangles)
# display the processed image
cv.imshow('Processed', processed_image)
cv.imshow('Matches', output_image)
# debug the loop rate
print('FPS {}'.format(1 / (time() - loop_time)))
loop_time = time()
# press 'q' with the output window focused to exit.
# waits 1 ms every loop to process key presses
if cv.waitKey(1) == ord('q'):
cv.destroyAllWindows()
break
class Movement:
# Properties
DEBUG = True
wincap = None
vision = None
bot = None
haystack_wnd = None
targetList = []
tooltipList = []
loginList = []
state = 0
isGood = False
loggingIn = False
points = []
current = ''
key = None
user = b'gAAAAABf470AGsKOJ65Ee9ZxZasRjABVUbdimwfivMloakcKoa20R_guknxp0K7xqYAbLD5IfZ9dUMJP77lKTM6oWRpYl17GHw=='
pw = b'gAAAAABf470AeGuSrJmZEZrBzs8rJEQqiUDUoArQPNSkMJnlaKyxEknOUXvtvpWlLbTqBkq0SnEnYvjadV7gFI1sd7jtJJbImQ=='
# Constructor
def __init__(self,
target='doodle.png',
tooltip='doodle.png',
haystack_wnd='Toontown Rewritten'):
self.haystack_wnd = haystack_wnd
# Our list of commands to execute in sequence
self.targetList = [
"targets/speedchat_bubble.png", "targets/Pets.png",
"targets/good.png", "targets/Tricks.png", "targets/Play_dead.png",
"targets/Scratch.png", "targets/Feed.png", "targets/Tired.png",
"targets/Excited.png"
]
self.tooltipList = [
"tooltips/tooltip.png", "tooltips/Pets_tt.png",
"tooltips/good_tt.png", "tooltips/Tricks_tt.png",
"tooltips/Play_dead_tt.png", "tooltips/Scratch_tt.png",
"tooltips/Feed_tt.png", "tooltips/Tired_tt.png",
"tooltips/Excited_tt.png"
]
# Window Capture has default to TTR, else we choose from main.
self.wincap = WindowCapture(window_name=haystack_wnd)
# WindowCapture.list_window_names()
# check foreground window title
current = self.wincap.title()
# Only two modes. Does not work from character select.
if (current == "Toontown Rewritten Launcher"):
self.login()
else:
self.vision = Vision(target)
self.bot = TTRBot((self.wincap.offset_x, self.wincap.offset_y),
(self.wincap.w, self.wincap.h))
# When giving our property objects new parameters
# we must stop and start again, otherwise "stopped"
# property gets reset to True.
self.wincap.start()
self.vision.start()
self.bot.start()
self.locator()
def command_chain(self, command, tooltip):
self.wincap.stop()
self.vision.stop()
self.bot.stop()
self.wincap = WindowCapture(window_name=self.haystack_wnd)
self.vision = Vision(command)
self.bot = TTRBot((self.wincap.offset_x, self.wincap.offset_y),
(self.wincap.w, self.wincap.h), tooltip)
self.wincap.start()
self.vision.start()
self.bot.start()
"""
Cryptology:
click.write_key()
key = click.load_key()
message1 = user.encode()
print(message1) - bytes now
message2 = pw.encode()
print(message2)
f = Fernet(key)
encrypted1 = f.encrypt(message1)
encrypted2 = f.encrypt(message2)
print(encrypted1)
print(encrypted2)
"""
def login(self):
# empty bits on bitmap, idk how they made the launcher
# self.locator()
# Just send input
# Decrypt our user name and pw. IF you want to continue,
# generate a new key for your own credentials; or remove the encryption all together.
self.key = self.load_key()
f = Fernet(self.key)
pdi.press(['tab'])
sleep(0.05)
pdi.typewrite(f.decrypt(self.user).decode())
sleep(0.05)
pdi.press(['tab'])
sleep(0.05)
pdi.typewrite(f.decrypt(self.pw).decode())
sleep(0.05)
pdi.press(['enter'])
sleep(0.05)
# Wait for TTR
self.wincap.wait_hwnd()
sleep(10.5)
pdi.press(['up'])
sleep(4.5)
self.wincap = WindowCapture(self.haystack_wnd)
self.vision = Vision("targets/bear.png")
self.bot = TTRBot((self.wincap.offset_x, self.wincap.offset_y),
(self.wincap.w, self.wincap.h),
'tooltips/tooltip_bear.png')
def locator(self):
# Too late, lazy to change variables from "self"
loop_time = time()
firstRun = True
while (True):
# All the classes run in their own thread that's separate from the main thread
# so that the code here can continue while the bot performs its actions
# if we don't have a screenshot yet, don't run the code below this point yet
if self.wincap.screenshot is None:
continue
# give vision the current screenshot to search for objects in
self.vision.update(self.wincap.screenshot)
# update the bot with the data it needs right now
if self.bot.state == BotState.INITIALIZING:
# while bot is waiting to start, go ahead and start giving it some targets to work
# on right away when it does start
targets = self.vision.get_click_points(self.vision.rectangles)
self.bot.update_targets(targets)
elif self.bot.state == BotState.SEARCHING:
# when searching for something to click on next, the bot needs to know what the click
# points are for the current detection results. it also needs an updated screenshot
# to verify the hover tooltip once it has moved the mouse to that position
targets = self.vision.get_click_points(self.vision.rectangles)
self.bot.update_targets(targets)
self.bot.update_screenshot(self.wincap.screenshot)
elif self.bot.state == BotState.MOVING:
# when moving, we need fresh screenshots to determine when we've stopped moving.
self.bot.update_screenshot(self.wincap.screenshot)
elif self.bot.state == BotState.STILL:
# nothing is needed while we wait for the ui to finish
"""
class Command:
OPTION = 0
PETS = 1
GOOD = 2
TRICKS = 3
TRICK = 4
TIRED = 5
SCRATCH = 6 - To save jellybeans.
FEED = 7
EXCITED = 8
"""
# Regular route - On successfull click
if not self.loggingIn:
if self.state + 1 < Command.EXCITED:
# Always do one round of excited check.
# Similar to bot's confirm_tooltip method
excited = cv.imread(self.targetList[Command.EXCITED],
cv.IMREAD_UNCHANGED)
excitement = cv.matchTemplate(self.wincap.screenshot,
excited,
cv.TM_CCOEFF_NORMED)
# get the best match postition
min_val, bestMatch, min_loc, max_loc = cv.minMaxLoc(
excitement)
if bestMatch >= 0.60:
# No need to feed if excited
if self.state == Command.FEED or self.state == Command.SCRATCH:
self.state = 0
self.isGood = False
# If we've already said "Good Boy!"
elif self.isGood and Command.GOOD:
self.state = Command.TRICKS
self.isGood = False
# If Good, then naw.
elif self.state == Command.GOOD:
self.isGood = True
self.command_chain(
command=self.targetList[self.state],
tooltip=self.tooltipList[self.state])
# If tired, or neutral, not good.
elif self.state == Command.FEED:
self.isGood = False
self.command_chain(
command=self.targetList[self.state],
tooltip=self.tooltipList[self.state])
else:
self.state = Command.SCRATCH
self.isGood = False
self.command_chain(
command=self.targetList[self.state],
tooltip=self.tooltipList[self.state])
# Increment after everything is done.
if firstRun:
firstRun = False
else:
self.state += 1
else:
self.isGood = False
self.state = Command.OPTION
self.command_chain(
command=self.targetList[self.state],
tooltip=self.tooltipList[self.state])
# Use loginList instead
else:
# for now
pass
if self.DEBUG:
# draw the detection results onto the original image
detection_image = self.vision.draw_rectangles(
self.wincap.screenshot, self.vision.rectangles)
# display the images
try:
cv.imshow('Matches', detection_image)
except:
pass
# sleep(0.5)
# win32gui.SetForegroundWindow(win32gui.FindWindow(None, "Toontown Rewritten"))
# debug the loop rate - bad atm
print('FPS {}'.format(1 / (time() - loop_time)))
print(self.state)
loop_time = time()
# Press 'q' with the output window focused to exit.
# Waits 1 ms every loop to process key presses
key = cv.waitKey(1)
if key == ord('q'):
self.wincap.stop()
self.vision.stop()
self.bot.stop()
cv.destroyAllWindows()
break
print('Done performing {} task.'.format(self.targetList[self.state]))
# Encrypts our user/pw
def write_key(self):
# Generates a key and save it into a file
self.key = Fernet.generate_key()
with open("key.key", "wb") as key_file:
key_file.write(self.key)
def load_key(self):
# Loads the key from the current directory named `key.key`
return open("key.key", "rb").read()
# when searching for something to click on next, the bot needs to know what the click
# points are for the current detection results. it also needs an updated screenshot
# to verify the hover tooltip once it has moved the mouse to that position
targets = vision.get_click_points(detector.rectangles)
bot.update_targets(targets)
bot.update_screenshot(wincap.screenshot)
elif bot.state == BotState.MOVING:
# when moving, we need fresh screenshots to determine when we've stopped moving
bot.update_screenshot(wincap.screenshot)
elif bot.state == BotState.MINING:
# nothing is needed while we wait for the mining to finish
pass
if DEBUG:
# draw the detection results onto the original image
detection_image = vision.draw_rectangles(wincap.screenshot,
detector.rectangles)
# display the images
cv.imshow('Matches', detection_image)
# press 'q' with the output window focused to exit.
# waits 1 ms every loop to process key presses
key = cv.waitKey(1)
if key == ord('q'):
wincap.stop()
detector.stop()
bot.stop()
cv.destroyAllWindows()
break
print('Done.')
cascade_limestone = cv.CascadeClassifier('result.xml')
# Carregue uma classe Vision
vision_limestone = Vision(None)
loop_time = time()
while (True):
# get an updated image of the game
imagem = wincap.get_screenshot()
# Detecção de objetos
rectangles = cascade_limestone.detectMultiScale(imagem)
# Desenha os resultados da detecção na imagem original
detection_image = vision_limestone.draw_rectangles(imagem, rectangles)
# Exibe a imagem
cv.imshow('Imagem', detection_image)
loop_time = time()
key = cv.waitKey(1)
# presionar Q para fecahr
if key == ord('q'):
cv.destroyAllWindows()
break
# F para salvar iamgem como positiva
elif key == ord('f'):
cv.imwrite('positiva/{}.jpg'.format(loop_time), imagem)
# D para salvar iamgem como negativa
# initialize the WindowCapture class
wincap = WindowCapture('2009scape')
cascade_iron = cv.CascadeClassifier("cascade/cascade.xml")
vision_iron = Vision(None)
loop_time = time()
while (True):
# get an updated image of the game
screenshot = wincap.get_screenshot()
rectangles = cascade_iron.detectMultiScale(screenshot)
detection_image = vision_iron.draw_rectangles(screenshot, rectangles)
cv.imshow("screenshot", detection_image)
# debug the loop rate
print('FPS {}'.format(1 / (time() - loop_time)))
loop_time = time()
# press 'q' with the output window focused to exit.
# waits 1 ms every loop to process key presses
key = cv.waitKey(1)
if cv.waitKey(1) == ord('q'):
cv.destroyAllWindows()
break
# Press F to save image containing image you want to be detected
elif key == ord("f"):
cv.imwrite("positive/{}.jpg".format(loop_time), screenshot)
# HSV filter to needle img
#hsv_filter = HsvFilter(0,0,0,0,0,0,0,0,0,0)
loop_time = time()
while (True):
screenshot = wincap.get_screenshot()
# cv.imshow('computer vision', screenshot)
# pre-process image
# processed_image = vision_friend.apply_hsv_filter(screenshot,hsv_filter)
#object detection
# Processed needle image finding
# rectangles = vision_friend.find(processed_image, threshhold=0.8)
rectangles = vision_friend.find(screenshot, threshhold=0.8)
# draw detection result on original image
output_image = vision_friend.draw_rectangles(screenshot, rectangles)
cv.imshow("matches", output_image)
print('FPS {}'.format(1 / (time() - loop_time)))
loop_time = time()
if cv.waitKey(1) == ord('q'):
cv.destroyAllWindows()
break
print('Done')
# USE THIS IF YOU ARE READING A VIDEO FILE
ret, smash_screenshot = cap.read()
# apply filter to img.
output_image = vision.apply_hsv_filter(smash_screenshot,
mario_training_filter)
move_locs[labels.neutral_b] = neutral_b.detectMultiScale(output_image)
move_locs[labels.jab] = jab.detectMultiScale(output_image)
move_locs[labels.shield] = sheild.detectMultiScale(output_image)
# select object to track.
tracker.track(output_image)
weights = 1
detection_image = vision.draw_rectangles(output_image, move_locs)
# JAB recenter tracker every time a jab is detected
if (len(move_locs[labels.jab]) > 0 and time() - t.last_jab > 1):
tracker.reset_tracker(output_image, move_locs[labels.jab])
count.jab += 1
t.last_jab = time()
# # NEUTRAL_B every 3 seconds
if (len(move_locs[labels.neutral_b]) > 0
and time() - t.last_neutral_b > 3):
count.neutral_b += 1
t.last_neutral_b = time()
# # SHEILD every 3 seconds
if (len(move_locs[labels.shield]) > 0 and time() - t.last_sheild > 1):
